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Principles of Database Management
The Practical Guide to Storing, Managing and Analyzing Big and Small Data

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  • Date Published: July 2018
  • availability: In stock
  • format: Hardback
  • isbn: 9781107186125

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  • This comprehensive textbook teaches the fundamentals of database design, modeling, systems, data storage, and the evolving world of data warehousing, governance and more. Written by experienced educators and experts in big data, analytics, data quality, and data integration, it provides an up-to-date approach to database management. This full-color, illustrated text has a balanced theory-practice focus, covering essential topics, from established database technologies to recent trends, like Big Data, NoSQL, and more. Fundamental concepts are supported by real-world examples, query and code walkthroughs, and figures, making it perfect for introductory courses for advanced undergraduates and graduate students in information systems or computer science. These examples are further supported by an online playground with multiple learning environments, including MySQL, MongoDB, Neo4j Cypher, and tree structure visualization. This combined learning approach connects key concepts throughout the text to the important, practical tools to get started in database management.

    • Contains extensive coverage of key trending topics, including data warehousing, data integration, data quality, data governance, Big Data, and analytics
    • Provides embedded state of the art research, including chapters on data integration, quality, and governance and analytics, which allows students to learn critical analysis of new developments in the field
    • Presents comprehensive coverage of database management fundamentals with a well-balanced theory-practice focus
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    Reviews & endorsements

    'Although there have been a series of classical textbooks on database systems, the new dramatic advances call for an updated text covering the latest significant topics, such as big data analytics, No-SQL and much more. Fortunately, this is exactly what this book has to offer. It is highly desirable for training the next generation of data management professionals.' Jian Pei, Simon Fraser University, Canada

    'I haven't seen an as up-to-date and comprehensive textbook for Database Management as this one in many years. Principles of Database Management combines a number of classical and recent topics concerning Data Modeling, Relational Databases, Object-Oriented Databases, XML, Distributed Data Management, NoSQL and Big Data in an unprecedented manner. The authors did a great job in stitching these topics into one coherent and compelling story that will serve as an ideal basis for teaching both introductory and advanced courses.' Martin Theobald, University of Luxembourg

    'This is a very timely book with outstanding coverage of database topics and excellent treatment of database details. It not only gives very solid discussions of traditional topics like data modeling and relational databases but also contains refreshing contents on frontier topics such as XML databases, NoSQL databases, big data, and analytics. For those reasons, this will be a good book for database professionals who will keep using it for all stages of database studies and works.' J. Leon Zhao, City University of Hong Kong

    'This accessible, authoritative book introduces the reader the most important fundamental concepts of data management, while providing a practical view of recent advances. Both are essential for data professionals today.' Foster Provost, New York University, Stern School of Business

    'This guide to big and small data management addresses both fundamental principles and practical deployment. It reviews a range of databases and their relevance for analytics. The book is useful to practitioners because it contains many case studies, links to open-source software, and a very useful abstraction of analytics that will help them better choose solutions. It is important to academics because it promotes database principles which are key to successful and sustainable data science.' Sihem Amer-Yahia, Laboratoire d'Informatique de Grenoble and Editor-in-Chief the International Journal on Very Large DataBases

    'This book covers everything you will need to teach in a database implementation and design class. With some chapters covering big data, analytic models/methods, and No-SQL, it can keep our students up-to-date with these new technologies in data management related topics.' Han-fen Hu, University of Nevada, Las Vegas

    'As we are entering a new technological era of intelligent machines powered by data-driven algorithms, understanding fundamental concepts of data management and their most current practical applications has become more important than ever. This book is a timely guide for anyone interested in getting up to speed with the state of the art in database systems, big data technologies, and data science. It is full of insightful examples and case studies with direct industrial relevance.' Nesime Tatbul, Intel Labs and Massachusetts Institute of Technology

    'It is a pleasure to study this new book on database systems. The book offers a fantastically fresh approach to database teaching. The mix of theoretical and practical contents is almost perfect, the content is up-to-date and covers the recent ones, the examples are nice, and the database testbed provides an excellent way of understanding the concepts. Coupled with the authors 'expertise, this book is an important addition to the database field.' Arnab Bhattacharya, Indian Institute of Technology, Kanpur

    'Principles of Database Management is my favorite textbook for teaching a course on database management. Written in a well-illustrated style, this comprehensive book covers essential topics in established data management technologies and recent discoveries in data science. With a nice balance between theory and practice, it is not only an excellent teaching medium for students taking information management and/or data analytics courses, but also a quick and valuable reference for scientists and engineers working in this area.' Chuan Xiao, Graduate School of Informatics, Nagoya University

    'Data science success stories and big data applications are only possible because of advances in database technology. This book provides both a broad and deep introduction to databases. It covers the different types of database systems (from relational to noSQL) and manages to bridge the gap between data modeling and the underlying basic principles. The book is highly recommended for anyone that wants to understand how modern information systems deal with ever-growing volumes of data.' Wil van der Aalst, RWTH Aachen University

    'The database field has been evolving for several decades and the need for updated textbooks is continuous. Now, this need is covered by this fresh book by Lemahieu, van den Broucke and Baesens. It spans from traditional topics - such as the relational model and SQL - to more recent topics – such as distributed computing with Hadoop and Spark as well as data analytics. The book can be used as an introductory text and for graduate courses.' Yannis Manolopoulos, Data Science & Engineering Lab, Aristotle University of Thessaloniki

    'I like the way the book covers both traditional database topics and newer material such as big data, No-SQL databases, and data quality. The coverage is just right for my course and the level of the material is very appropriate for my students. The book also has clear explanations and good examples.' Barbara Klein, University of Michigan

    This book provides a unique perspective on database management and how to store, manage, and analyze small and big data. The accompanying exercises and solutions, cases, slides, and YouTube lectures turn it into an indispensable resource for anyone teaching an undergraduate or postgraduate course on the topic.' Wolfgang Ketter, Erasmus University Rotterdam

    'This is a very modern textbook that fills the needs of current trends without sacrificing the need to cover the required database management systems fundamentals.' George Dimitoglou, Hood College, Maryland

    'This book is a much needed foundational piece on data management and data science. The authors successfully integrate the fields of database technology, operations research and big data analytics, which have often been covered independently in the past. A key asset is its didactical approach that builds on a rich set of industry examples and exercises. The book is a must-read for all scholars and practitioners interested in database management, big data analytics and its applications.' Jan Mendling, Institute for Information Business, Vienna

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    Product details

    • Date Published: July 2018
    • format: Hardback
    • isbn: 9781107186125
    • dimensions: 253 x 194 x 34 mm
    • weight: 1.91kg
    • contains: 439 colour illus. 163 tables
    • availability: In stock
  • Table of Contents

    Preface
    Part I. Databases and Database Design:
    1. Fundamental concepts of database management
    2. Architecture and categorization of DBMSs
    3. Conceptual data modeling using the (E)ER model and UML class diagram
    4. Organizational aspects of data management
    Part II. Types of Database Systems:
    5. Legacy databases
    6. Relational databases: the relational model
    7. Relational databases: structured query language (SQL)
    8. Object oriented databases and object persistence
    9. Extended relational databases
    10. XML databases
    11. NoSQL databases
    Part III. Physical Data Storage, Transaction Management, and Database Access:
    12. Physical file organization and indexing
    13. Physical database organization
    14. Basics of transaction management
    15. Accessing databases and database APIs
    16. Data distribution and distributed transaction management
    Part IV. Data Warehousing, Data Governance and (Big) Data Analytics:
    17. Data warehousing and business intelligence
    18. Data integration, data quality and data governance
    19. Big data
    20. Analytics
    Appendix A. Cases and questions
    Appendix B. Using the online environment
    Appendix C. Answer key to select review questions
    Glossary
    Index.

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    Principles of Database Management

    Wilfried Lemahieu, Seppe vanden Broucke, Bart Baesens

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  • Authors

    Wilfried Lemahieu, KU Leuven, Belgium
    Wilfried Lemahieu is a professor at KU Leuven, Belgium, Faculty of Economics and Business, where he also holds the position of Dean. His teaching, for which he was awarded a 'best teacher recognition' includes courses on database management, enterprise information management and management informatics. His research focuses on big data storage and integration, data quality, business process management and service-oriented architectures. In this context, he collaborates extensively with a variety of industry partners, both local and international. His research is published in renowned international journals and he is a frequent lecturer for both academic and industry audiences.

    Seppe vanden Broucke, KU Leuven, Belgium
    Seppe vanden Broucke works as an assistant professor at the Faculty of Economics and Business, KU Leuven, Belgium. His research interests include business data mining and analytics, machine learning, process management and process mining. His work has been published in well-known international journals and presented at top conferences. He is also author of the book Beginning Java Programming (2015) of which more than 4000 copies were sold and which was also translated in Russian. Seppe's teaching includes advanced analytics, big data and information management courses. He also frequently teaches for industry and business audiences.

    Bart Baesens, KU Leuven, Belgium
    Bart Baesens is a professor of Big Data and Analytics at KU Leuven, Belgium and a lecturer at the University of Southampton. He has done extensive research on big data and analytics, credit risk modeling, fraud detection and marketing analytics. He has written more than 200 scientific papers some of which have been published in well-known international journals (e.g. MIS Quarterly, Machine Learning, Management Science, MIT Sloan Management Review and IEEE Transactions on Knowledge and Data Engineering) and presented at international top conferences (e.g. ICIS, KDD, CAISE). He received various best paper and best speaker awards. Bart is the author of 6 books: Credit Risk Management: Basic Concepts (2009), Analytics in a Big Data World (2014), Beginning Java Programming (2015), Fraud Analytics using Descriptive, Predictive and Social Network Techniques (2015), Credit Risk Analytics (2016) and Profit-Driven Business Analytics (2017). He sold more than 15.000 copies of these books worldwide, some of which have been translated in Chinese, Russian and Korean.

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